Personal details

Name
Dr Tobias Fischer
Position(s)
Research Fellow
Science and Engineering Faculty,
School of Electrical Engineering & Robotics
Discipline *
Artificial Intelligence and Image Processing, Electrical and Electronic Engineering
Phone
+61 7 3374 1463
Email
Location
View location details (QUT staff and student access only)
Identifiers and profiles
ORCID iD Twitter LinkedIn
Qualifications

Doctor of Philosophy (Imperial College, London), M.Sc. (University of Edinburgh), B.Sc. (Other)

Professional memberships
and associations
  • Fellow, Higher Education Academy (FHEA)
  • Member, Institution of Engineering and Technology (MIET)
  • Member, Institute of Electrical and Electronics Engineers (IEEE)
  • Member, British Machine Vision Association (BMVA)
  • Member, IEEE Robotics and Automation Society
Keywords

Robotics, Computer Vision, Computational Cognition, Perspective Taking, Gaze Estimation

* Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2008

Biography

Research Overview

Dr Tobias Fischer conducts interdisciplinary research at the intersection of computer vision, cognitive robotics and computational cognition. His research goal is to provide robots with perceptional abilities that allow interactions with humans in a human-like manner. To develop these perceptional abilities, Tobias believes that it is useful to study the principles used by the animal visual system. He uses these principles to develop new computer vision algorithms and validates their effectiveness in intelligent robotic systems.

Research Experience

Dr Fischer was a co-author and named lead researcher of two applications for the Samsung Global Research Outreach program, which resulted in 200,000 USD commercial funding. In addition, he has been working on major research projects funded by European Union FP7 and H2020 programs, and the Multidisciplinary University Research Initiative (MURI).

His papers have received two best poster awards:

  • Samsung AI Forum 2018 for the paper entitled “Context-aware Deep Feature Compression for High-speed Visual Tracking” (appeared at CVPR2018)
  • IEEE International Conference on Computer Vision 2019 Workshop on Gaze Estimation and Prediction in the Wild for the paper entitled “RT-BENE: A Dataset and Baselines for Real-Time Blink Estimation in Natural Environments”

Career History

Before joining QUT as a Research Fellow in January 2020, Dr Fischer was a postdoctoral researcher in the Personal Robotics Lab at Imperial College London. He received a PhD from Imperial College with the thesis topic: “Perspective Taking in Robots: A Framework and Computational Model” in January 2019. The thesis has been awarded the Queen Mary UK Best Thesis in Robotics Award 2018 and the Eryl Cadwaladr Davies Prize for the best thesis in the Electrical and Electronic Engineering Department at Imperial College 2018.

Dr Fischer received the M.Sc. degree in Artificial Intelligence from The University of Edinburgh, in August 2014, and a B.Sc. degree in Computer Engineering from Ilmenau University of Technology, Germany, in 2013. He wrote his Bachelor thesis in John Tsotsos’ Lab for Active and Attentive Vision, at the York University, Canada. From February 2012 until August 2014, he was a scholarship holder at the prestigious German National Academic Foundation (Studienstiftung des Deutschen Volkes).

Web Links

Publication highlights

  1. Fischer & Demiris: Computational Modelling of Embodied Visual Perspective-taking (IEEE Transactions on Cognitive and Developmental Systems)
  2. Fischer, Chang & Demiris: RT-GENE: Real-Time Eye Gaze Estimation in Natural Environments (European Conference on Computer Vision ECCV2018)
  3. Fischer, Moulin-Frier et al.: DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self (IEEE Transactions on Cognitive and Developmental Systems 2018)
  4. Choi et al.: Context-aware Deep Feature Compression for High-speed Visual Tracking (IEEE Conference on Computer Vision and Pattern Recognition CVPR2018)
  5. Chang, Fischer, Petit, Zambelli and Demiris: Learning Kinematic Structure Correspondences Using Multi-Order Similarities (IEEE Transactions on Pattern Analysis and Machine Learning TPAMI2018 & CVPR2016)
This information has been contributed by Dr Tobias Fischer.

Teaching

Dr Fischer’s teaching profile accounts for over 75 hours of teaching in a wide range of undergraduate and postgraduate courses. He also regularly supervises PhD, MSc/MEng and BSc/BEng students, and mentors lab members on an ongoing basis to support their success. Dr Fischer is a Fellow of the Higher Education Academy which demonstrates his overall commitment to professionalism in learning and teaching.

Teaching Overview:

  • Guest Lecturer, Human-Centered Robotics, Autumn 2019 (Imperial College London)
  • Assessor, Mobile Healthcare and Machine Learning, Spring 2019 (Imperial College London)
  • Assessor, Human-Centered Robotics, Autumn 2018 (Imperial College London)
  • Tutor, Object-Oriented Programming, Spring 2014 (University of Edinburgh)
  • Tutor, Processing Formal and Natural Languages, Autumn 2013 (University of Edinburgh)
  • Tutor, Software Engineering, Autumn 2013 (University of Edinburgh)
  • Tutor, Algorithms and Programming, Autumn 2011 (Ilmenau University of Technology)
  • Tutor, Algorithms and Programming, Autumn 2010 (Ilmenau University of Technology)

Supervision Overview:

  • PhD student: “Real-Time Multi-Person Pose Tracking using Data Assimilation” (WACV2020 proceedings paper), Imperial College London, 2017 – 2019
  • Research assistant on the PAL H2020 project: “Real-Time Knowledge-ability Prediction on Mobile Devices”, Imperial College London, 2018 – 2019
  • BEng in Electrical and Electronic Engineering: “Use of Gaze Estimation in Mobile Learning Environments to Infer Text Comprehension”, Imperial College London, 2019
  • MEng in Informatics and Systems Modeling: “Fusing Linguistic and Gaze Information for Human Robot Interaction” (ICCV2019 workshop proceedings paper best poster award)Imperial College London, 2018
  • MEng in Electrical and Electronic Engineering: “Comper: A Collaborative Musical Accompaniment System using Deep Latent Vector Models”, Imperial College London, 2018
  • MSc in Computing: “Towards Verbal Control of Humanoid Robots”, Imperial College London, 2018
This information has been contributed by Dr Tobias Fischer.

Publications

For publications by this staff member, visit QUT ePrints, the University's research repository.